This inventor holds 1 USPTO granted patent. Top assignee: Accenture Global Solutions Limited. Active years: 2023.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:
Years Active: 2023
Title: Manish Kumar - Innovator in Material Failure Forecasting
Introduction
Manish Kumar is a notable inventor based in Navi Mumbai, India. He has made significant contributions to the field of material failure forecasting. His innovative approach utilizes historical failure data to predict future failures, enhancing reliability in various applications.
Latest Patents
Manish Kumar holds a patent for a system titled "Forecasting failures of interchangeable parts." This material failure forecasting system analyzes historical failure data using text processing techniques. It identifies failures and suspensions by recognizing fault words associated with negations. The system establishes a fault ontology that categorizes different failure modes into primary, secondary, and tertiary levels. This categorization enables the identification of a sequence of failures. The identified failures are fitted to a selected data distribution, which is then used to simulate a demand profile for the material, considering interchangeability. Additionally, the failure data of materials in equipment can be analyzed to estimate the reliability of that equipment.
Career Highlights
Manish Kumar is currently employed at Accenture Global Solutions Limited, where he applies his expertise in material failure forecasting. His work focuses on improving the reliability of materials and equipment through innovative forecasting techniques.
Collaborations
Some of his coworkers include Hitesh Bhagchandani and Rajarajan Thangavel Ramalingam. Their collaboration contributes to the advancement of technology in their field.
Conclusion
Manish Kumar's innovative work in forecasting material failures demonstrates his commitment to enhancing reliability in engineering applications. His contributions are valuable to the industry and showcase the importance of predictive analytics in material science.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
